Artificial Intelligence in Infectious Disease Clinical Practice: An Overview of Gaps, Opportunities, and Limitations

Overview

Journal Trop Med Infect Dis

Specialty Infectious Diseases

Date 2024 Oct 25

PMID 39453255

Authors

Andreas Sarantopoulos

Christina Mastori Kourmpani

Atshaya Lily Yokarasa

Chiedza Makamanzi

Polyna Antoniou

Nikolaos Spernovasilis

Constantinos Tsioutis

Affiliations

Soon will be listed here.

Abstract

The integration of artificial intelligence (AI) in clinical medicine marks a revolutionary shift, enhancing diagnostic accuracy, therapeutic efficacy, and overall healthcare delivery. This review explores the current uses, benefits, limitations, and future applications of AI in infectious diseases, highlighting its specific applications in diagnostics, clinical decision making, and personalized medicine. The transformative potential of AI in infectious diseases is emphasized, addressing gaps in rapid and accurate disease diagnosis, surveillance, outbreak detection and management, and treatment optimization. Despite these advancements, significant limitations and challenges exist, including data privacy concerns, potential biases, and ethical dilemmas. The article underscores the need for stringent regulatory frameworks and inclusive databases to ensure equitable, ethical, and effective AI utilization in the field of clinical and laboratory infectious diseases.

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